Yuhong Liu

Yuhong Liu
Santa Clara University | SCU · Department of Computer Engineering

Doctor of Engineering

About

55
Publications
9,574
Reads
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610
Citations
Citations since 2017
47 Research Items
577 Citations
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2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150

Publications

Publications (55)
Chapter
The proliferation of smart home Internet of Things (IoT) devices is demonstrated by their prominence in people’s lives. However, the resource-constraint essence of these devices introduces various security flaws. One significant attack is the Low-rate Distributed Denial of Service (LR-DDoS) attack, which aims to disrupt the functionalities of the s...
Article
Full-text available
Deep learning has shown remarkable advantages in many fields. Although the image recognition capabilities and deep neural network (DNN) have developed rapidly in recent years, relevant studies have confirmed that DNN will be attacked by well-crafted images, resulting in model recognition errors. The adversarial examples generated by the traditional...
Article
5G and Internet of Things (IoT) are closely related and promote each other. Network Slice (NS) technology based on Software Defined Network (SDN) and Network Function Virtualization (NFV) have changed the traditional network architecture. Subsequently, the secure access authentication of IoT terminals for 5G networks and the selection of network sl...
Article
Full-text available
Employing edge and fog computing for building IoT systems is essential, especially because of the massive number of data generated by sensing devices, the delay requirements of IoT applications, the high burden of data processing on cloud platforms, and the need to take immediate actions against security threats.
Article
Full-text available
User behavior prediction with low-dimensional vectors generated by user network embedding models has been verified to be efficient and reliable in real applications. However, existing graph representation learning methods mainly focus on homogeneous and static graphs and cannot well represent the real-world social networks that are heterogeneous an...
Preprint
Resource sharing among users serves as the foundation of cloud computing, which, however, may also cause vulnerabilities to diverse co-residence attacks launched by malicious virtual machines (VM) residing in the same physical server with the victim VMs. In this paper, we aim to defend against such co-residence attacks through a secure, workload-ba...
Article
Full-text available
Resource sharing among users serves as the foundation of cloud computing, which, however, may also cause vulnerabilities to diverse co-residence attacks launched by malicious virtual machines (VM) residing in the same physical server with the victim VMs. In this paper, we aim to defend against such co-residence attacks through a secure, workload-ba...
Article
Full-text available
Considering the resource constraints of Internet of Things (IoT) stations, establishing secure communication between stations and remote servers imposes a significant overhead on these stations in terms of energy cost and processing load. This overhead, in particular, is considerable in networks providing high communication rates and frequent data...
Article
Full-text available
As one of the hot research directions in natural language processing, sentiment analysis has received continuous and extensive attention. Different from explicit sentiment words indicating sentiment polarity, implicit sentiment analysis is a more challenging problem due to the lack of sentiment words, which makes it inadequate to use traditional se...
Preprint
With the rise in Internet of Things (IoT) devices, home network management and security are becoming complex. There is an urgent requirement to make smart home network management efficient. This work proposes an SDN-based architecture to secure smart home networks through K-Nearest Neighbor (KNN) based device classifications and malicious traffic d...
Preprint
Full-text available
Mirai is a type of malware that creates a botnet of internet-connected devices, which can later be used to infect other devices or servers. This paper aims to analyze and explain the Mirai code and create a low-cost simulation environment to aid in the dynamic analysis of Mirai. Further, we perform controlled Denial-of-Service attacks while measuri...
Preprint
Full-text available
IoT devices have become popular targets for various network attacks due to their lack of industry-wide security standards. In this work, we focus on smart home IoT device identification and defending them against Distributed Denial of Service (DDoS) attacks. The proposed framework protects smart homes by using VLAN-based network isolation. This arc...
Article
Full-text available
Nowadays, more people are used to express their attitudes on different entities in online social networks, forming user-to-entity sentiment links. These sentiment links imply positive or negative semantics. Most of current user sentiment analysis literature focuses on making a positive, neutral, or negative sentiment decision according to users’ te...
Article
Digital signature is a major component of transactions on Blockchain platforms, especially in enterprise Blockchain platforms, where multiple signatures from a set of peers need to be produced to endorse a transaction. However, such process is often complex and time-consuming. Multi-signature, which can improve transaction efficiency by having a se...
Conference Paper
Full-text available
Mirai is a type of malware that creates a botnet of internet-connected devices which can later be used to infect other devices or servers. The objectives of this paper are to analyze and explain the Mirai code, to create a low-cost simulation environment to aid in the dynamic analysis of Mirai, and to perform controlled Denial-of-Service attacks wh...
Article
Full-text available
Stock market prediction has been identified as a very important practical problem in the economic field. However, the timely prediction of the market is generally regarded as one of the most challenging problems due to the stock market’s characteristics of noise and volatility. To address these challenges, we propose a deep learning-based stock mar...
Article
Full-text available
Sentiment analysis has become a very popular research topic, especially for retrieving valuable information from various online environments. Most existing sentiment studies are based on supervised learning, which requires sufficient amount of labeled data. However, sentiment analysis often faces insufficient labeled data in practice, as it is very...
Chapter
With a large number of connected Internet of Things (IoT) devices deployed across the world, they have become popular targets of malicious attacks raising great security challenges. Many manufacturers are making great efforts to keep the software on these devices up-to-date to protect the security of these IoT devices. However, the software update...
Conference Paper
Full-text available
The Transport Layer Security (TLS) protocol has been considered as a promising approach to secure Internet of Things (IoT) applications. The different cipher suites offered by the TLS protocol play an essential role in determining communication security level. Each cipher suite encompasses a set of cryptographic algorithms, which can vary in terms...
Conference Paper
In this paper, we propose GraphSE\textsuperscript2, an encrypted graph database for online social network services to address massive data breaches. GraphSE\textsuperscript2 ~preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and me...
Article
Full-text available
The dimension reduction of large scale high-dimensional data is a challenge task, especially the dimension reduction of face data and the accuracy increment of face recognition in large scale face recognition system, which may cause large storage space and long recognition time. In order to further reduce the recognition time and the storage space...
Preprint
In this paper, we propose GraphSE$^2$, an encrypted graph database for online social network services to address massive data breaches. GraphSE$^2$ preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and com...
Article
Device-to-device (D2D) communication has been increasingly attractive due to its great potential to improve the cellular communication performance. While resource-allocation optimization for improving the spectrum efficiency is of interest in D2D-related work, the communication security, as a key issue in the system design, has not been well invest...
Article
Full-text available
Cloud computing is clearly one of today’s most enticing technologies due to its scalable, flexible, and cost-efficient access to infrastructure and application services. Despite these benefits, cloud service users (CSUs) have serious concerns about the data security and privacy. Currently, there are several cloud service providers (CSPs) offering a...
Article
Recommender systems have the effect of guiding users to interesting objects in a large space of possible options based on their preferences. However, providing accurate recommendations for new users, who do not have any records, is one of the most challenging problems in recommender systems. To retrieve sufficient information of the new users, exis...
Article
Full-text available
Presidential elections can impact world peace, global economics, and overall well-being. Recent news indicates that fraud on the Web has played a substantial role in elections, particularly in developing countries in South America and the public discourse, in general. To protect the trustworthiness of the Web, in this paper, we present a novel fram...
Article
In this paper, we propose a General Non-negative Matrix Factorization based on the left Semi-Tensor Product (lGNMF) and the General Non-negative Matrix Factorization based on the right Semi-Tensor Product (rGNMF), which factorize an input non-negative matrix into two non-negative matrices of lower ranks based on gradient method. In particular, the...
Article
Collaborative filtering has become one of the most widely used methods for providing recommendations in various online environments. Its recommendation accuracy highly relies on the selection of appropriate neighbors for the target user/item. However, existing neighbor selection schemes have some inevitable inadequacies, such as neglecting users' c...
Article
Community mining for complex social networks with link and attribute information plays an important role according to different application needs. In this paper, based on our proposed general non-negative matrix factorization (GNMF) algorithm without dimension matching constraints in our previous work, we propose the joint GNMF with graph Laplacian...
Article
In this paper, we propose a novel general non-negative matrix factorization (general-NMF)-based digital watermarking scheme for copyright protection and integrity authentication of the image content. Specifically, the proposed general-NMF algorithm is able to factorize a matrix C ∈ R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="...
Article
Community mining for complex social networks with link and attribute information plays an important role according to different application needs. In this paper, based on our proposed general non-negative matrix factorization (GNMF) algorithm without dimension matching constraints in our previous work, we propose the joint GNMF with graph Laplacian...
Article
The prosperity of online rating system makes it a popular place for malicious vendors to mislead public’s online decisions, whereas the security related studies are lagging behind. In this work, we develop a quantile regression model to investigate influential factors on online user choices and reveal that the promotion effect on products’ market o...
Conference Paper
Collaborative filtering has become one of the most widely used methods for providing recommendations in various online environments. Its recommendation accuracy highly relies on the selection of appropriate neighbors for the target user/item based on a user-item matrix. However, existing neighbor selection schemes have inevitable inadequacies, espe...
Article
Full-text available
While cloud computing is gaining popularity, diverse security and privacy issues are emerging that hinder the rapid adoption of this new computing paradigm. And the development of defensive solutions is lagging behind. To ensure a secure and trustworthy cloud environment it is essential to identify the limitations of existing solutions and envision...
Article
Full-text available
Manipulating online ratings of a product, in terms of both volume and value, can substantially influence its market performance, but the profits of a particular strategy can vary across products and might not be maximized by the highest rating values.
Conference Paper
Full-text available
In the IT world of corporate networking, how businesses store and compute data is starting to shift from in-house servers to the cloud. However, some enterprises are still hesitant to make this leap to the cloud because of their information security and data privacy concerns. Enterprises that want to invest into this service need to feel confident...
Conference Paper
Full-text available
With the rapid development of cloud computing, more users are attracted by its powerful and cost-efficient computation capability. However, whether CSPs can effectively protect CSUs’ data confidentiality remains a challenging issue. In this work, we aim at ensuring data confidentiality in the cloud environment by enabling CSUs to (1) encrypt their...
Article
As computing and communication systems evolve rapidly and ubiquitously, it has become convenient and almost effortless for individual users to generate, share, and exchange information on online social media. Through online social media, a wide range of digital content, which covers blogging, forums, reviews, social networking, question-answer data...
Article
With the rapid development of reputation systems in various online social networks, manipulations against such systems are evolving quickly. In this paper, we propose scheme TATA, the abbreviation of joint Temporal And Trust Analysis, which protects reputation systems from a new angle: the combination of time domain anomaly detection and Dempster-S...
Conference Paper
With the big success of the mobile application (app) sales, attackers are also attracted by the potential profits in the app market. In this paper, we survey current app ranking schemes as well as existing app reputation manipulation schemes and raise some interesting while arguable questions. Based on an app installation data set collected from a...

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